This study investigates an approach of knowledge discovery and data mining in insufficient databases. An application of Computational Taxonomy analysis demonstrates that the approach is effective in such a data mining process. The approach is characterized by the use ot…

In this position paper, the main steps to measure and evaluate quantitatively the quality of sites are shown. Besides, some specific models, criteria and procedures to apply in these activities are discussed by quoting case studies already performed (e.g., in…

Vertical partitioning, in which attributes of a relation are
assigned to partitions, is aimed at improving database
performance. We extend previous research that is based on
a single relation to multi-relation database environment,
by including referential integrity constraints, access time

Data integration is the process of unifying data sharing some common semantics but are originated from unrelated sources. In our work we consider these sources are autonomous, heterogeneous and they are physically distributed. These three characteristics make the integration task…

Similarity search is a fundamental operation for applications that deal with unstructured data sources. In this paper we propose a new pivot-based method for similarity search, called Sparse Spatial Selection (SSS).
The main characteristic of this method is that it…

The Semantic Web attempts to reach a state in the future where everything on the Web will no longer be only machine-readable, but also machine-understandable. An ontology is an explicit specification of a conceptualization. A conceptualization is an abstract, simplified…

In situ hybridization (ISH) method allows to reveal specific genes expression, identify specific cell types and detect areas or tissues, displaying differential gene expression. This work describes a standardized procedure of digital image processing that allows detailed analyses of ISH…

This book provides an excellent foundation for the principles of database and data management. It explains some of the more difficult concepts fairly well. The book is meant for an introductory course in database management which is usually required as…

Nowadays, data intensive applications are in constant demand and there is need of computing environments with better intelligent capabilities than those present in today's Database Management Systems (DBMS). To build such systems we need formalisms that can perform complicate inferences,…

This paper presents a data structure based on Sparse Spatial Selection (SSS) for similarity searching. An algorithm that tries periodically to adjust pivots to the use of database index is presented. This index is dynamic. In this way, it is…